A typical prior art space-time adaptive processing (STAP) system includes an array of N transmit and receive antennas. The antenna array can be mounted on a moving platform, e.g., a plane or a boat, to locate air, ground and sea targets. STAP systems are also used by meteorologists and geologists.
The receiver antenna gain pattern can be steered in a desired direction by a beam forming process. Advanced STAP systems are required to detect targets in the presence of both clutter and jamming. Ground or sea clutter is extended in both angle and range, and is spread in Doppler frequency because of the platform motion.
The STAP system uses a pulse train, and coherent pulse integration. A coherent processing interval (CPI) defines the duration of the pulse train. During each CPI, the transmitter sends out M pulses using the transmit antennas. The time between the beginning of a pulse and the beginning of the next pulse is called a pulse repetition interval (PRI). The pulses reflect from targets at different distances from the STAP system.
The range to a target is determined by the time interval between the sending of a pulse and receiving the reflected signal. The STAP system collects the reflected signals for each antenna, or each pulse and range. The data derived from the reflected signals can be assembled into a three-dimensional matrix, which is sometimes called a STAP cube.
The problem solved by the invention is shown schematically in FIG. 1. In sensing applications built on a moving platform, returned signals are commonly contaminated by clutter returns in the form of interference 101, which decreases the signal-to-noise ratio (SNR) from different incoming angles 102 and Doppler frequencies 103. To accurately locate moving targets, effective clutter suppression techniques are indispensable.
Among the many known clutter-suppression techniques, space-time adaptive processing (STAP) is the most promising. In STAP, returned signals are filtered simultaneously over space and time domains. As a result, clutter interference can be effectively suppressed regardless of the incoming angle and Doppler frequency.
However, the conventional STAP is handicapped by a prohibitive computational complexity. For M pulses and N antennas, the conventional STAP requires an intensive matrix inversion of dimension MN×MN. For practical systems with MN on the order of hundreds, such a large matrix inversion requirement makes it difficult to implement STAP for real-time target detection.
To circumvent this obstacle, considerable research efforts have been devoted to developing low-complexity STAP. According to Brennan's rule, the rank of the clutter interference covariance matrix C is known to be much smaller than MN. Thus, one way to achieve complexity reduction is to compress the returned signal into an r-dimensional subspace with r<<MN. In particular, one low-complexity STAP exploits a subspace tracking called fast approximated power iteration (FAPI). FAPI can be employed to effectively compress the returned signal into a much smaller signal subspace, which enables low-complexity STAP operating on the compressed data.